---
license: mit
base_model: ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: best_berita_roberta_model_fold_5
  results: []
---

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# best_berita_roberta_model_fold_5

This model is a fine-tuned version of [ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa](https://huggingface.co/ayameRushia/roberta-base-indonesian-sentiment-analysis-smsa) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1318
- Accuracy: 0.9808
- Precision: 0.9811
- Recall: 0.9807
- F1: 0.9807

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5679        | 1.0   | 601  | 0.1942          | 0.9425   | 0.9449    | 0.9419 | 0.9419 |
| 0.2491        | 2.0   | 1202 | 0.1654          | 0.9692   | 0.9691    | 0.9694 | 0.9691 |
| 0.1085        | 3.0   | 1803 | 0.1314          | 0.9742   | 0.9743    | 0.9741 | 0.9740 |
| 0.074         | 4.0   | 2404 | 0.2535          | 0.9575   | 0.9604    | 0.9568 | 0.9564 |
| 0.0255        | 5.0   | 3005 | 0.1318          | 0.9808   | 0.9811    | 0.9807 | 0.9807 |
| 0.0164        | 6.0   | 3606 | 0.1795          | 0.9759   | 0.9762    | 0.9756 | 0.9756 |
| 0.0           | 7.0   | 4207 | 0.2299          | 0.9725   | 0.9730    | 0.9723 | 0.9721 |
| 0.0039        | 8.0   | 4808 | 0.2241          | 0.9717   | 0.9723    | 0.9714 | 0.9713 |
| 0.0048        | 9.0   | 5409 | 0.2199          | 0.9717   | 0.9723    | 0.9714 | 0.9713 |
| 0.0           | 10.0  | 6010 | 0.2303          | 0.9717   | 0.9723    | 0.9714 | 0.9713 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1